Discrete-space versus continuous-space lesion boundary and area definitions.
Discrete-space versus continuous-space lesion boundary and area definitions.
复制标题
离散空间与连续空间病变边界和区域定义。
DOI：
10.1118/1.2963989
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发表时间：
2008
期刊：
影响因子：
3.8
通讯作者：
Armato3rd,SamuelG
中科院分区：
文献类型：
--
作者：
Sensakovic,WilliamF;Starkey,Adam;Roberts,RachaelY;Armato3rd,SamuelG
测量医学图像中感兴趣的解剖区域的大小用于诊断疾病，跟踪生长和评估对治疗的反应。医学图像的离散性质允许区域边界的连续和离散定义。这些定义可以反过来支持几种面积计算方法，这些方法给出的定量值有很大的不同。本研究探讨了几种边界定义（如连续多边形、内部离散和外部离散）和面积计算方法（像素计数和格林定理）。这些方法应用于三个独立的数据库：一个合成图像数据库，肺图像数据库联盟肺结节数据库和肾上腺轮廓数据库。在应用于临床数据库的不同方法中，发现面积的平均差异为20%左右。这些结果支持了区域边界定义和面积计算不一致的应用可能会严重影响测量精度的观点。
Measurement of the size of anatomic regions of interest in medical images is used to diagnose disease, track growth, and evaluate response to therapy. The discrete nature of medical images allows for both continuous and discrete definitions of region boundary. These definitions may, in turn, support several methods of area calculation that give substantially different quantitative values. This study investigated several boundary definitions (e.g., continuous polygon, internal discrete, and external discrete) and area calculation methods (pixel counting and Green's theorem). These methods were applied to three separate databases: A synthetic image database, the Lung Image Database Consortium database of lung nodules and a database of adrenal gland outlines. Average percent differences in area on the order of 20% were found among the different methods applied to the clinical databases. These results support the idea that inconsistent application of region boundary definition and area calculation may substantially impact measurement accuracy.